Communication theory will be applied to the study of the visual system to: o Develop a visual sensitivity chart which "bypasses" the optics of the eye. Thresholds in noise are remarkably insensitive to optical deficits. We will test and further develop a letters-in-noise test chart which exploits this fact to assess visual performance in the presence of impaired optics. Theory and pilot data show that performance is almost totally unaffected by optical deficits, implying that patients with below normal letter-in-noise sensitivity must have neural deficits, either retinal or central. The test chart has potential for assessing vision even in the presence of dense cataracts, and may have diagnostic value in distinguishing different kinds of natural deficit. o Measure the information capacity of visual attention. We hypothesize that the information capacity of visual attention can be characterized by how much information capacity is required at the display for optimal performance of an attentive task by the observer. We predict that this information capacity will be constant, on the order of 100 bits, for all visual tasks requiring attention. Twelve experiments will test will hypothesis by measuring the required information capacity for a wide variety of visual tasks. o Extract structure from motion. We will investigate motion and depth preception of human and machine vision systems when images are restricted by low resolution, low contrast, small visual field, or temporal blurring. We will use existing motion algorithms to extract 3-dimensional structure from a two-dimensional velocity flow field. Human performance at the same task will be compared to that of the algorithm. The results will test existing structure-from-motion algorithms as models of motion and depth perception in the human visual system.